Welcome to this Cloud Wars Agent and Copilot Minute. In these discussions, I’ll be analyzing opportunities, impact, and outcomes possible with AI; today’s focus is AI agent definitions and use cases.
Highlights
00:40 — There’s a lack of a universal definition for AI agents. An agent pursues a goal given to it, reasons across systems, and makes judgment calls to achieve that goal, regardless of whether it is fully autonomous or not. I’m going to explain four AI agents ranging from least to most autonomous.
01:25 — The credit reference agent automates the manual process of gathering and formatting payment history information for customer references. This low level of autonomy is where I recommend most companies start in their AI agent journey: streamlining repetitive, manual tasks, improving efficiency, and reducing errors.
02:01 — Our competitor research agent automates the process of gathering and synthesizing data about competitors. It takes in a competitor and a question, conducts research, and produces a document for the user. It requires more judgment and flexibility in its actions, making it more autonomous.
02:30 — The Fabric health monitoring agent runs on a cadence to monitor the data environment and surface issues that need attention. It automates the process of checking dashboards and identifying problems before they become critical, improving the timeliness and effectiveness of issue resolution. It’s an example of how AI can shift from reactive to proactive maintenance.
02:56 — Our personal assistant agent monitors the user’s inbox, team chats, calendar, and active projects to identify what needs their attention. It’s the most autonomous of the four, providing a comprehensive overview of the user’s workload and prioritizing tasks based on their importance. It’s designed to act as a chief of staff, managing the user’s workflow and ensuring they stay focused on high-priority tasks.
04:04 — AI agents not only save time but also help regain attention, which is a valuable resource that cannot be easily bought. Measuring the value of AI agents in terms of attention rather than efficiency can lead to better decisions about which agents to build.
More CIO and AI Agent Insights:
- 4 Requirements to Drive Results That Go Beyond ‘AI Theater’
- AI Delivers Big Wins When You Select The Best Tool for the Job
- How AI Diagnosed a Fabric Capacity Problem for Quick Resolution
- Copilot’s Advantage vs. Stand-Alone Chatbots
For a 36-Hour Immersion into the FY27 Priorities that define Partner Success in the AI Era, join us at the AI Business Solutions Partner Executive Summit, running July 22-23, 2026, in Bellevue, Washington. Register today.
Kenny Mullican
CIO
Paragon Films
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